Global Virtual Event

Introduction to NLP models and vector search

Hosted by

Headshot
Tom Grabowski

Principal Product Manager

Elastic

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Nick Chow

Prinicipal Product Manager

Elastic

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Gilad Gal

Product Manager, Elasticsearch

Elastic

Overview

Introducing modern NLP and native vector search in Elasticsearch. Leverage new ML models to understand context, increase speed and improve results. Unlock advanced text analytics like named entity recognition (NER), semantic text embedding, emotion and sentiment analysis, or text classification with significantly less effort and time. Start with pre-built models or scale your own.

Highlights:

  • How to leverage Lucene 9 and dense vector fields
  • NLP examples for named entity recognition, text classification, and text embedding
  • Working with NLP, HuggingFace, and PyTorch models
  • Using vectors and NLP to create modern semantic search applications

Additional resources:

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